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Found 6 papers, 2 papers with code
Unsupervised Contrastive Analysis for Salient Pattern Detection using Conditional Diffusion Models
In this work, we redefine the CA task by employing a self-supervised contrastive encoder to learn a latent representation encoding only common patterns from input images, using samples exclusively from the BG dataset during training, and approximating the distribution of the target patterns by leveraging data augmentation techniques.
Hierarchical Object-Centric Learning with Capsule Networks
First, we explore the effectiveness of the routing algorithm, particularly in small-sized networks.
AI-Assisted Diagnosis for Covid-19 CXR Screening: From Data Collection to Clinical Validation
In this paper, we present the major results from the Covid Radiographic imaging System based on AI (Co. R. S. A.)
Towards Efficient Capsule Networks
From the moment Neural Networks dominated the scene for image processing, the computational complexity needed to solve the targeted tasks skyrocketed: against such an unsustainable trend, many strategies have been developed, ambitiously targeting performance's preservation.
Lung nodules segmentation from CT with DeepHealth toolkit
The accurate and consistent border segmentation plays an important role in the tumor volume estimation and its treatment in the field of Medical Image Segmentation.
REM: Routing Entropy Minimization for Capsule Networks
This paper proposes REM, a technique which minimizes the entropy of the parse tree-like structure, improving its explainability.
